Detection error analysis. We analyze the different types of detection errors using the tool proposed by [1]} for the baseline SSD300 and the distilled models with our KD\(_{cls}\)  + \(loc\)  + KD\(_{loc}\) . We focus on the classification and localization errors, which are the main errors in object detection. The details of all error types are provided in the supplementary material. As shown in Figure REF a, KD\(_{cls}\)  decreases the classification error especially for IoUs smaller than 0.65. By contrast, as shown in Figure REF b, the effect of KD\(_{loc}\)  increases with the IoU. This again shows the complementary nature of these terms.
